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Practical deep learning for cloud, mobile, and edge : real-world AI and computer-vision projects using Python, Keras and TensorFlow

Author: Anirudh Koul; Siddha Ganju; Meher Kasam
Publisher: Sebastopol : O'Reilly Media, Incorporated, [2019] ©2019
Edition/Format:   eBook : Document : English : First EditionView all editions and formats
Summary:

This step-by-step guide teaches you how to build practical deep learning applications for the cloud and mobile using a hands-on approach.

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Genre/Form: Electronic books
Additional Physical Format: Print version:
Koul, Anirudh.
Practical Deep Learning for Cloud, Mobile, and Edge : Real-World AI and Computer-Vision Projects Using Python, Keras and TensorFlow.
Sebastopol : O'Reilly Media, Incorporated, ©2019
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Anirudh Koul; Siddha Ganju; Meher Kasam
ISBN: 9781492034810 1492034819 9781492034834 1492034835
OCLC Number: 1124616548
Notes: Includes index.
Description: 1 online resource (xvi, 586 pages) : illustrations
Contents: Exploring the landscape of Artificial Intelligence --
What's in the picture: image classification with Keras --
Cats versus dogs: transfer learning in 30 lines with Keras --
Building a reverse image search engine: understanding embeddings --
From novice to master predictor: maximizing convolutional neural network accurcy --
Maximizing speed and performance of TensorFlow: a handy checklist --
Practical tools, tips, and tricks --
Cloud APIs for computer vision: up and running in 15 minutes --
Scalable inference serving on Cloud with TensorFlow Serving and KubeFlow --
AI in the browser with TensorFlow.js and mI5.js --
Real-time object classification on iOS with Core ML --
Not hotdog on iOS with Core ML and Create ML --
Shazam for food: developing android apps with TensorFlow Lite and ML Kit --
Building the purrfect cat locator app with TensorFlow Object Detection API --
Becoming a maker: exploring embedded AI at the edge --
Simulating a self-driving car using end-to-end deep learning with Keras --
Building an autonomous car in under an hour: reinforcement learning with AWS DeepRacer
Responsibility: Anirudh Koul, Siddha Ganju and Meher Kasam.
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